Digital Commons Network^™

Adaptive Image Acquisition Algorithms For Resource-Constrained Single-Photon Cameras, Yeganeh Jalalpour, Wu-Chi Feng

Computer Science Faculty Publications and Presentations

Emerging single-photon camera (SPC) technologies have unique challenges in data acquisition and processing. Unlike conventional sensors that produce a single 8- to 16-bit brightness value per pixel, SPCs record photon arrivals with many more samples per pixel, using high floating-point precision for each photon collected. This means that they must handle potentially millions of timestamps, especially at higher spatial resolutions and in the presence of ambient light, creating bottlenecks within the pixel circuitry. To address these challenges associated with SPCs, this paper proposes adaptive algorithms designed to efficiently distribute hardware resources among groups of pixels. By selectively subsampling the data …

Examining The Intersectional And Structural Issues Of Routine Healthcare Utilization And Access Inequities For Lgb People With Chronic Diseases, Shiya Cao, Mehreen Mirza, Sophia Silovsky, Nicole Tresvalles, Lucia Qin, Sarah Susnea

Statistical and Data Sciences: Faculty Publications

In the United States, although the gaps in health insurance coverage by sexual orientation have been closing since the implementation of the Affordable Care Act and legalization of same-sex marriage, the LGB group (i.e., lesbian, gay, bisexual) continues to report healthcare utilization and access inequities such as more delayed or unmet care. The extant research has often examined healthcare utilization and access inequities due to affordability (e.g., out-of-pocket costs). However, healthcare utilization and access inequities are only partially explained by cost reasons; there are non-cost reasons that have not been adequately empirically examined. The present study innovatively includes discrimination structural …

Hint-Guided Video Frame Interpolation For Video Compression, Pan Tan, Wu-Chi Feng

Computer Science Faculty Publications and Presentations

Traditional video compression continues to advance, but the gainsin efficiency are diminishing and come at the cost of higher compu-tational complexity. Despite achieving competitive rate-distortionresults, current neural video codecs (NVCs) generally lack sup-port for a wide range of quality levels, often requiring multiplemodels to achieve flexible rate control, which increases both train-ing cost and deployment complexity. To address the limitations ofboth traditional codecs and current NVCs, we propose a hybridvideo compression framework that integrates traditional codecswith hint-guided video frame interpolation (VFI), a learning-basedtechnique for synthesizing intermediate frames. By using decodedreference frames and leveraging compressed-domain hints to guideinterpolation, our method improves …

Exploring Healthcare Providers' Perceptions Of Virtual Reality In Lung Cancer Treatment Preparedness: A Mixed-Methods Feasibility Study For The Development Of Everybreathmatters, Safa Elkefi, Rongyi Wu, Steven K. Feiner, Lanyi Chen, Guy Hembroff, Alicia K. Matthews

Michigan Tech Publications

This study examined healthcare providers' perceptions of the benefits, challenges, and design preferences for Virtual Reality (VR)-based interventions to support treatment preparedness in lung cancer care. Our study involves 50 surveys and 10 interview responses, in a mixed-method design. We conducted descriptive statistics and thematic analysis through a hybrid inductive-deductive approach. Analysis of the quantitative data helped us capture demographic characteristics, VR familiarity, and perceived VR usefulness. Qualitative analysis gave us a deeper understanding of the VR tool design and Implementation. Descriptive statistics and Fisher's exact tests were used to assess associations, while thematic analysis was conducted on interview transcripts. …

A Predictive Model For Multi- Week Respiratory Risk From Red Tide On Florida’S Gulf Coast., Elmer S. Ochaeta

Computer Science and Engineering Faculty Publications

Florida’s Gulf Coast red tide (Karenia brevis) can put toxins into the air, making people cough, irritating the throat, and worsening asthma or other breathing problems especially when winds blow from the ocean toward the beach. Right now, most public updates don’t really help with the question people actually ask when planning a weekend or vacation: “Will going to or close to the beach be risky in the next few weeks?”.

In this project, I build a weekly early warning system that estimates respiratory risk for specific beaches and predicts that risk 2 to 4 weeks ahead. The study covers …

Enhancing Breast Cancer Detection In Mammographic Imaging Using Explainable Clinical Decision Support System And Framework, Ahed Abugabah, Prashant Kumar Shukla, Piyush Kumar Shukla, Abhishek Dwivedi

All Works

Breast cancer remains one of the leading causes of mortality among women worldwide, where early and precise detection plays a vital role in improving survival rates and treatment outcomes. However, conventional deep learning approaches often encounter challenges in handling dense mammographic tissues and lack transparency in decision-making, limiting their clinical reliability. To address these limitations, this study introduces TransYOLO-GJO, an explainable and optimized detection framework that integrates transformer-based attention mechanisms into the YOLOv9 architecture and leverages the Golden Jackal Optimization (GJO) algorithm for hyperparameter tuning. The transformer encoder enhances contextual feature extraction, particularly in dense breast regions, while GJO dynamically …

Capstone Reflection: Developing A Muslim Prayer App For Psu Students, Jeremiah Su

University Honors Theses

This thesis examines the development process of the Muslim Student Association (MSA) App, a computer science capstone project. The app strives to help the Muslim community at Portland State University (PSU) and the Portland area by consolidating essential information for prayers, such as local prayer times, nearby masjids, and the direction of Qibla. The team behind this project was developed by 6 computer science developers, a majority of whom were from the Muslim culture and background. This paper describes the entire capstone development process from the perspective of a developer who is not rooted in Muslim customs. It also describes …

Establishing Convergence Thresholds For Pre-Trajectory Sampling With Batched Execution Across Random Quantum Circuits, Taylor L. Eskew, Jerome F. Gonthier, Taylor L. Patti, Andrew N. Jordan

Student Scholar Symposium Abstracts and Posters

A crucial aspect of validating quantum protocols is understanding the noise produced by quantum computing devices. Using simulations that can replicate this noise allows for a lower-cost alternative to hardware experiments. Stochastic, so-called "trajectory" methods are often used as a quadratically reduced approximation to density matrix simulations, but traditional implementations have limited sampling capacity and provide no error-based metadata. The Pre-Trajectory Sampling with Batched Execution (PTSBE) [Patti et al., 2025] algorithm provides a solution by combining fine-tuned, well-documented noise sampling with computational intermediate caching.

While the original work is effective on quantum error correction circuits, its performance on general circuits …

Gamification Of A Bimanual Coordination Task, Robby Johnson, Caeden Kidd, Johnathan Oestringer, Jaylin Pigeon, Brandon Woolman

Infinite Loop

Video games are a promising future for research and development. A new way to measure motor skills is to use robots to test individuals. This technology is incredible and has helped the medical field, but there must be a way to allow individuals to use this technology in a similar and affordable manner. Space Trash is a game that was developed with the intent to gamify the object hit detection that is used in the Kin Arm Robot with the intent to see if a person will show signs of Alzheimer’s. The goal is to not only be able to …

A Proposed Study Of Tone Indicators In Sentimental Analysis And Emotion Detection, Andrea Llanas

Infinite Loop

Sentimental analysis and emotion detection have been an ever-growing field in academic literature in recent years [1,2,3]. There are many methods and techniques to distinguish positive and negative tokens as well as classification of emotions respectively. However, the use of tone indicators has been relatively underexplored within the field.

Tone indicators are a relatively recent trend in social media. Users denote a positive or negative connotation as well as an emotion in a sentence at the moment of conception with syntax such as “/s,” “/pos,” and “/neg.” These annotations often are context-free, or do not depend on previously declared information, …

Business Financial Information Systems, Lirie Koraqi, James Jolovski Prof.

International Journal of Business and Technology

An information system is a combination of software, hardware, and telecommunication networks to collect useful data, especially in an organisation. Many businesses use information technology to complete and manage their operations, interact with their consumers, and stay ahead of their competition. Some companies today are completely built on information technology.

Well designed and implemented business information systems should provide the information management and outside parties need to make informed and timely decisions about the operating health of the company. Business considers the need to have information available to assess the profitability of a new product they are selling or their …

Digital Transformation Management And Organizational Performance: The Case Of Albanian Healthcare Sector, Oltjan Hamza

International Journal of Business and Technology

Purpose - The integration of digital technologies into the healthcare system is essential for improving both operational efficiency and quality of services. This study examines the relationship between digital transformation management and organizational performance in the healthcare sector in Albania, with particular focus on the mediating role of leadership in digital transformation and the digital skills of the healthcare staff. Methodology - The study employ a quantitative method through a structured questionnaire using a Likert scale, which was distributed to 93 healthcare sector employees in public and private institutions in Albania. Findings - Data collected through the survey were analyzed …

Applied Cryptography With Python, Hizer Leka, Albiona Leka

International Journal of Business and Technology

Cryptography is a key aspect of information security and provides data security. This paper aims to provide a better understanding of cryptography and its application with Python through real life examples. It covers the basics of cryptography, containing information about symmetric and asymmetric encryption methods. Throughout the paper we dive into different encryption methods, from simple to more complex, starting with the Caesar Cipher that has been used by people ever since ancient times, the Reverse Cipher which is one of the simplest encryption methods, all the way to implementing a RSA Algorithm using Python’s cryptography library, always providing knowledge …

Supply Chain Attacks Through Open Source Software: A Comprehensive Analysis Of Npm, Pypi, And Docker Hub Vulnerabilities, Thomas Pham

Cybersecurity Undergraduate Research Showcase

Open-source software ecosystems have become critical infrastructure for modern software development, yet they remain vulnerable to sophisticated supply chain attacks. This paper presents a comprehensive empirical analysis of supply chain attacks targeting npm, PyPI, and Docker Hub, examining 23 documented campaigns affecting over 2.6 billion weekly downloads. Through systematic analysis of attack vectors including typosquatting, dependency confusion, and maintainer account compromise, we identify recurring patterns and structural vulnerabilities across package registries. Our analysis reveals that 86.1% of detected typosquatted packages contained malware, with cryptocurrency theft emerging as the predominant attack objective. We document the September 2025 npm compromise affecting 18 …

Viability Of Widely Used Encryption Schemes In Drone Transmission, Emanuel Yasir Nelson

Cybersecurity Undergraduate Research Showcase

This paper presents throughout research on the security issues related to drone transmission. These topics were addressed and explained, in particular the aspects relating to cybersecurity, for utmost clarity. These include threats and vulnerabilities, drone transmission the impact of encryption on latency, and the details of the encryption methods AES-128, AES-256, and ChaCha20 that were used in the experiment described in the paper. Each encryption method performance was measured and outputted by the Python code developed and used in the experiment. Afterwards, the performance of each method was analyzed in relation to their decryption time, encryption time, end to end …

Decoding The Chameleon Game, Tri Dang '25, Hieu Tran, Brian T. Howard, Sutthirut Charoenphon, Dat Nguyen '25

Student Research

The Chameleon game is a challenging word association activity where players are given a secret word and must respond with words relevant to that secret word. It requires strategic thinking and deduction. The Chameleon must cleverly guess the secret keyword in this game while avoiding suspicion. Our research aims to create an advanced artificial intelligence (AI) model that can play the Chameleon game from both perspectives: as the Chameleon and as a Human. This AI is designed to guess secret keywords based on the information provided by the players, choose the best strategies to avoid detection as the Chameleon, identify …

Explainable Ai For Liver Transplant Survival Prediction: Integrating Immunological Mismatch Features, Sourab Shaik

Honors Projects

Liver Transplantations are crucial treatment for end-stage liver disease. However, a persistent deficit of donor organs necessitates maximizing the utility of each available graft to minimize failure rates. We evaluated whether donor–recipient molecular immunogenicity metrics - Electrostatic and Hydrophobic Mismatch Scores (HMS/EMS) and eplet-based counts - improve post–liver-transplant survival prediction. The analytic cohort comprised adult, first time, single-organ deceased-donor transplants drawn from Scientific Registry of Transplant Recipients; follow-up was truncated at five years, and the endpoint was all-cause graft failure (earliest of graft failure or death; otherwise, censored). HLA variables were derived via high- resolution conversion and molecular mismatch computations …

Experience From A Distance: Improving Transparency For The Multnomah Athletic Club, Matthew Penner

University Honors Theses

Portland is home to the largest and one of the most prestigious athletic clubs in the world: Multnomah Athletic Club. In many ways, it is the pinnacle of luxury and innovation, and over time, it finds any way to entice prospective members to pay the expensive upfront fee of $6000 and monthly membership fees exceeding $300. Due to the previous technological barrier, which was not being able to see the full extent of what amenities the club had to offer, the club faced major challenges in recruitment and marketing. Over two academic terms, a team of six computer science capstone …

The Artificial Intelligence (Ai) Economy In The Mountain West, 2025, Dre Boyd-Weatherly, Sean Curry, Krish Sharma, Kristian Thymianos, William E. Brown Jr.

Economic Development & Workforce

This fact sheet reports on the artificial intelligence (AI) readiness of five Mountain West metropolitan statistical areas (MSAs): Phoenix-Mesa-Chandler, AZ; Salt Lake City-Murray, UT; Denver-Aurora-Centennial, CO; Las Vegas-Henderson-North Las Vegas, NV; and Albuquerque, NM. Using data from the Brookings Institution's “Mapping the AI Economy” report, the MSAs are benchmarked based on their overall population, employment, talent, adoption, and innovation.

Developing Accessible Narrative-Based Stem Learning Software For K-6 Braille Display Users, Dylan Ravel, Daniel Tsivkovski, Brandon Foley, Maryam Etezad, Franceli Cibrian, Ariel Han, Rajeev Joshi

Student Scholar Symposium Abstracts and Posters

This research develops a free, accessible web application that enables K-6 students who are blind or visually impaired (BVI) to learn STEM concepts using refreshable braille displays. Currently, most online learning tools are not designed for BVI students, creating a significant educational barrier.

The application interfaces with commercial braille displays and uses narrative-based learning to make STEM content approachable and engaging. By presenting material as interactive stories, students can connect with concepts while developing braille reading skills. The curriculum design prioritizes accessibility through the Accessible Rich Internet Applications (ARIA) standards and screen reader support.

The goal is to provide BVI …

Bridging Machine Learning And Islamic Scholarship: A Study In Hadith Translation And Similarity Analysis, Asiyah R. Speight

Student Scholar Symposium Abstracts and Posters

Translation of Islamic religious texts poses unique challenges requiring both linguistic and theological expertise. This study explores the application of neural machine translation (NMT) models to Arabic-English hadith translation while analyzing semantic similarity patterns across different human translations. Using the complete Sahih Bukhari corpus (7,550 hadiths) as the primary dataset, we adopt a dual approach combining transfer learning and comprehensive neural network analysis to demonstrate the critical impact of corpus size on model performance.

First, we fine-tune a pre-trained MarianMT Arabic-English translation model on the full Sahih Bukhari corpus, comparing models trained on 40 hadiths versus 7,550 hadiths. Performance is …

Understanding Medical Information And Emotional Support Needs In Mental Health Questions With Large Language Models, Chen Liu, William Yu Chung Wang, Gohar Khan

All Works

Purpose – This study seeks to bridge the gap between users’ multidimensional needs and the single-task capabilities of existing Mental Health Question Answering (MHQA) systems by tackling the underexplored challenge of jointly understanding medical informational needs and emotional support needs within complex consumer mental health inquiries. Design/methodology/approach – Grounded in Rhetorical Structure Theory (RST), the proposed Multi-Needs and Context Recognition (MNCR) framework decomposes mental health question understanding task into four interrelated subtasks: Medical Needs Recognition (MNR), Medical Needs-related Context Extraction (MNCE), Emotional Needs Recognition (ENR) and Emotional Needs-related Context Extraction (ENCE). A new benchmark dataset, MHQ-MedEmo, was constructed through multi-layered …

Efficient Routing For Software-Defined Wireless Sensor Networks: A Naïve Bayes Approach, Amine Tcherak, Samia Loucif, Mohamed Ould Khaoua

All Works

Wireless Sensor Networks (WSNs) form the backbone of Internet of Things (IoT) applications. Software-Defined Networking (SDN) is an emerging networking paradigm that extends the lifetime of WSNs by transferring the resource-intensive routing task from sensor nodes to a centralized controller. However, many SDN-based routing schemes for WSNs employ inefficient algorithms at the controller. Traditional shortest-path methods often create traffic imbalances across neighboring nodes, while Reinforcement Learning (RL)-based approaches typically generate excessive control traffic. Both issues accelerate energy depletion and reduce network lifetime. Moreover, existing algorithms frequently overlook critical factors, such as buffer occupancy, when selecting relay nodes, which can lead …

Iso-Detr: A Novel Detection Transformer For Industrial Small Object Detection, Faisal Saeed, Anand Paul

School of Public Health Faculty Publications

Effectively detecting and assessing real-time structural and ecological parameters in contemporary manufacturing environments poses significant challenges, particularly in identifying minute objects within product images. The swift evolution of the industrial sector underscores the necessity for intelligent manufacturing environments to uphold stringent product quality standards. However, accelerating production processes at high speeds heightens the risk of defective product outcomes. This research addresses the challenges inherent in small object detection within industrial contexts, proposing an innovative detection transformer model tailored to modern manufacturing environments. The proposed model integrates a feature-enhanced multi-head self-attention block (FEMSA), merging cross-channel communication network and multiple multi-head self-attention …

Confidential, Attestable, And Efficient Inter-Cvm Communication With Arm Cca, Sina Abdollahi, Amir Al Sadi, Marios Kogias, Hamed Haddadi, David Kotz

Other Faculty Materials

Confidential Virtual Machines (CVMs) are increasingly adopted to protect sensitive workloads from privileged adversaries such as the hypervisor. While they provide strong isolation guarantees, existing CVM architectures lack first-class mechanisms for inter-CVM data sharing due to their disjoint memory model, making inter-CVM data exchange a performance bottleneck in compartmentalized or collaborative multi-CVM systems. Under this model, a CVM's accessible memory is either shared with the hypervisor or protected from both the hypervisor and all other CVMs. This design simplifies reasoning about memory ownership; however, it fundamentally precludes plaintext data sharing between CVMs because all inter-CVM communication must pass through hypervisor-accessible …

Rogue Access Points And Their Impact On Networks, Sami Belmokhtar

Cybersecurity Undergraduate Research Showcase

This paper focuses on rogue access points (rogue APs) and how they can impact the security and stability of a network, and consequently, the safety and privacy of the users. Wireless access points (WAPs) are nodes that allow a user to connect to a local network. This includes devices such as the routers typically used in a home network. This paper examines how an unauthorized WAP may pose a threat to a network in both a public environment and an enterprise environment. Furthermore, it shows how a hacker can mimic a real wireless network and gain access to both user …

Early Career Setback And Future Achievement In Professional Sports, Suman Kalyan Maity, Yang Wang, Nima Dehmamy, Victoria Medvec, Brian Uzzi, Dashun Wang

Computer Science Faculty Research & Creative Works

A central tenet of human performance posits that past success is a key predictor of future outcomes. This principle underpins selection processes in various human endeavors, shaping opportunity, wage, and winner-take-all inequalities. Here we systematically examine the future performance of previous winners and non-winners across two sports contexts using two different empirical strategies. First, we track young athletes participating in world-class track and field competitions and compare the future performance of bronze medalists to those finishing just shy of the podium. Next, we study a novel natural experiment in tennis, where we compare future performances of 'lucky losers'—players who advanced …

Large Language Models As Machines Of Beauty: Cognitive Averaging, Latent Space Geometry, And The Entropic Foundations Of Aesthetic Preference, Daniel Plate, James Hutson

Faculty Scholarship

This study advances the position that large language models (LLMs) and human perceptual systems are governed by a shared computational drive toward prototypicality, entropy reduction, and aesthetic coherence. Drawing on developmental evidence that infants exhibit early preferences for facial symmetry and averageness, the analysis situates aesthetic preference within broader research on processing fluency and predictive coding, emphasizing that biological perception rewards stimuli that reduce uncertainty and support efficient information compression. This foundation is used to examine how LLMs, through cross-entropy optimization, perplexity minimization, and latent space clustering, converge on high-density representational regions that operate as statistical prototypes of linguistic and …

Sme Cyber Resilience State Of The Sector 2025, Hazel Murray, Gillian O'Carroll, Aoibheann Brangan, Jason Holland, Stephanie Chevanne Wallace, Miriam Curtain, Glenda Deveney

Department of Computer Science Publications

Ireland's small and medium enterprises (SMEs) face a critical cyber resilience gap. SMEs account for 99.8% of all enterprises in Ireland and employ over 2.29 million people, representing 67.9% of total employment (based on the latest CSO 2022 figures). This cyber resilience assessment reveals that the majority of SMEs remain underprepared for modern cyber threats.

(R2131) Analysis Of Map/Ph/1 Retrial Inventory Queueing System With Constant Retrial Rate, Bernoulli Vacation, Breakdown, Delayed Repair, Balking, (S, S) Policy And Emergency Replenishment, G. Ayyappan, M. Thilakavathy

Applications and Applied Mathematics: An International Journal (AAM)

A single server retrial queueing-inventory model is investigated in this study. In Bernoulli vacation, after providing service to the customer, the server may opt to avail vacation or start the service to subsequent customer. During the busy period, breakdown and balking may occur. The inventory is replenished to an (s, S) policy and the replenishing time is assumed to adopt an exponential distribution. Furthermore, assume that an emergency replenishment of one item with zero lead time takes place when the on-hand inventory level decreases to zero. We integrate the emergency replenishment into the system to ensure customer satisfaction. For our …